AI services
AI services for practical workflow improvement
We help businesses identify the right AI opportunities, build useful AI-assisted applications and put the right controls around them.
The work runs across operations, sales, ecommerce, finance, marketing, customer service, product, reporting and admin. We work around the systems your team already uses: spreadsheets, CRM, ERP, PIM, WMS, ecommerce platforms, reporting tools, supplier data and internal knowledge bases.
We start with the business problem, not the AI model. WithPraxis is model and platform agnostic.
Core services
- AI opportunity and ROI assessment
- Build AI applications
- AI workflow automation
- System and data integration
- AI governance and guardrails
- Microsoft Copilot readiness assessment
- How we work
Supporting service pages below give detail on specific areas.
AI Readiness Assessment
Working with leadership and operational teams to identify the workflows and tasks where AI is genuinely useful, not just theoretically possible. Includes current-state mapping, ownership clarification, use case identification and ROI modelling.
A clear list of high-impact workflows where AI can help, with named owners and success metrics. Not a deck - a working document.
- Timeline:
- 2-4 weeks
- Deliverable:
- Workflow map with prioritised opportunities, named owners and ROI estimates
Workflow Mapping & AI Readiness
Mapping the workflows and tasks that matter most across your teams, who owns them, what information they need and where the gaps are. Interviews, observation and data analysis to surface what is really happening.
Visual map of workflow flows, dependencies and breakpoints. Forms the foundation for everything else.
- Timeline:
- 3-6 weeks
- Deliverable:
- Visual map of workflow flows, dependencies and breakpoints with recommendations
Data Quality & Migration
Getting data into usable shape, audits for completeness and accuracy, deduplicates records, normalises formats, migrates from legacy systems. Prerequisite work before AI or integration projects can succeed.
Clean, normalised data ready for AI tools and workflow support. Derisks subsequent projects and eliminates manual cleanup cycles.
- Timeline:
- 4-8 weeks
- Deliverable:
- Cleaned data, quality reports, validation documentation, schema definitions and governance recommendations
AI Governance & Policy Development
Practical guardrails for AI use, use case evaluation criteria, approval workflows, data access controls, incident response procedures. Operational policy that helps teams move forward safely.
Operational AI governance framework with clear policies and approval workflows. Accelerates deployment by giving teams clear boundaries.
- Timeline:
- 3-6 weeks
- Deliverable:
- AI governance policy documentation, use case evaluation framework, approval workflows, data access controls, incident response procedures
How this actually works
Most engagements start with assessment - 2-4 weeks understanding your workflows and where AI helps. Build work runs 2-4 months, in cycles: build small, test with real users, refine.
Expect honest timelines, realistic expectations, and work that actually gets finished.
Not sure where to start?
"The phased approach worked. We validated value in the first 4 weeks before committing to full build. That de-risked the investment significantly."
Finance Director, Manufacturing (Global)
Common questions about working together
Common questions about working together
What kind of AI services does WithPraxis provide?
Practical AI services for workflows, tasks and teams. We cover AI workflow audits, AI readiness assessments, custom assistants, automation of repetitive tasks, product and supplier data work, reporting support and integration around the systems you already use.
Where does a typical engagement start?
Most engagements start with one workflow or task where AI could save time, reduce manual effort or improve visibility. We map the work, check the data and systems involved, then build something small, useful and measurable before scaling.
Do we need a workflow audit before anything else?
Not always. If you already know the workflow that needs improving, we can start there. A workflow audit is useful when the team knows the pain but is not yet sure which task or process to tackle first.
How does the AI readiness assessment fit in?
The readiness assessment is a structured way to look at where you are with data, systems, governance and people, and to surface the workflows where AI is genuinely useful. It is a starting point, not a prerequisite.
Which departments do you support?
We work across operations, sales, ecommerce, finance, marketing, customer service, product, reporting and admin. The shared pattern is teams slowed down by repetitive work, fragmented data or disconnected systems.
What systems and data do you work with?
We work around spreadsheets, CRM, ERP, PIM, WMS, ecommerce platforms, reporting tools and supplier data. The aim is to make existing systems more useful, not to replace them.
How do you roll out AI in a controlled way?
Each engagement defines clear inputs, human review where it matters, sensible approvals and a measurable outcome. We start small, prove the workflow, then extend it once the team is confident.
What practical outcomes should we expect?
Typical outcomes include time saved on repetitive tasks, faster reporting, cleaner product or supplier data, better customer responses and fewer manual handovers between teams.
How does an engagement work end to end?
We agree the workflow, map the data and systems, build something useful, add human review where needed, measure the outcome and then decide whether to extend it. The aim is practical improvement, not a long programme of work.
Related across WithPraxis